4,556 research outputs found
COEL: A Web-based Chemistry Simulation Framework
The chemical reaction network (CRN) is a widely used formalism to describe
macroscopic behavior of chemical systems. Available tools for CRN modelling and
simulation require local access, installation, and often involve local file
storage, which is susceptible to loss, lacks searchable structure, and does not
support concurrency. Furthermore, simulations are often single-threaded, and
user interfaces are non-trivial to use. Therefore there are significant hurdles
to conducting efficient and collaborative chemical research. In this paper, we
introduce a new enterprise chemistry simulation framework, COEL, which
addresses these issues. COEL is the first web-based framework of its kind. A
visually pleasing and intuitive user interface, simulations that run on a large
computational grid, reliable database storage, and transactional services make
COEL ideal for collaborative research and education. COEL's most prominent
features include ODE-based simulations of chemical reaction networks and
multicompartment reaction networks, with rich options for user interactions
with those networks. COEL provides DNA-strand displacement transformations and
visualization (and is to our knowledge the first CRN framework to do so), GA
optimization of rate constants, expression validation, an application-wide
plotting engine, and SBML/Octave/Matlab export. We also present an overview of
the underlying software and technologies employed and describe the main
architectural decisions driving our development. COEL is available at
http://coel-sim.org for selected research teams only. We plan to provide a part
of COEL's functionality to the general public in the near future.Comment: 23 pages, 12 figures, 1 tabl
DNA Computing and Implementations
DNA Computing aims to harness the molecules at the Nano level for computational purpose. DNA Computing features high data density and massive storage capability therefore, its approach can be used to solve various combinatorial Problems like solving Non Deterministic Problems (i.e. NP- Complete and NP-Hard). This Molecular Level Computational involve input and output both in the molecule form. Since DNA has already been explored as an exquisite material and is a fundamental block for manufacturing large scale Nano mechanical devices. DNA Computing is an approach towards the Biomolecular Computation where the aim is not only to process the information but also to transfer it to other molecular structures for utilization. DNA Computing is slower when an individual DNA Computes in compare to silica based chips. Its Efficiently and throughput increases as the number of DNA increase. DNA provides the possibility of massive parallelism. Starting with the Introduction about the DNA Structure, followed up by DNA Computers, this paper will discuss some recent advancements and challenges of DNA Computing. We will also discuss the possible future scope and implementation as well how the Artificial Intelligence approach can be used with DNA Based Computers to achieve a better and efficient Machine Learning
Programmability of Chemical Reaction Networks
Motivated by the intriguing complexity of biochemical circuitry within individual cells we study Stochastic Chemical Reaction Networks (SCRNs), a formal model that considers a set of chemical reactions acting on a finite number of molecules in a well-stirred solution according to standard chemical kinetics equations. SCRNs have been widely used for describing naturally occurring (bio)chemical systems, and with the advent of synthetic biology they become a promising language for the design of artificial biochemical circuits. Our interest here is the computational power of SCRNs and how they relate to more conventional models of computation. We survey known connections and give new connections between SCRNs and Boolean Logic Circuits, Vector Addition Systems, Petri Nets, Gate Implementability, Primitive Recursive Functions, Register Machines, Fractran, and Turing Machines. A theme to these investigations is the thin line between decidable and undecidable questions about SCRN behavior
Molecular Logic Computation with Debugging Method
Seesaw gate concept, which is based on a reversible DNA strand branch process, has been found to have the potential to be used in the construction of various computing devices. In this study, we consider constructing full adder and serial binary adder, using the new concept of seesaw gate. Our simulation of the full adder preformed properly as designed; however unexpected exception is noted in the simulation of the serial binary adder. To identify and address the exception, we propose a new method for debugging the molecular circuit. The main idea for this method is to add fan-outs to monitor the circuit in a reverse stepwise manner. These fan-outs are fluorescent signals that can obtain the real-time concentration of the target molecule. By analyzing the monitoring result, the exception can be identified and located. In this paper, examples of XOR and serial binary adder circuits are described to prove the practicability and validity of the molecular circuit debugging method
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